We study how noisy flows impact the prices of the cross-section of assets, particularly through the interaction between the factor structure of flows and the assets’ risk structure. In our new framework, systematic flows into systematic risk factors generate a factor model of price impacts. We develop empirical methods for the model by introducing flows into classical portfolio tools, including the Sharpe ratio, Fama-MacBeth regression, Fama-French portfolios, and Gibbons-Ross-Shanken test. We estimate the model using U.S. equity mutual fund flows data. The model-implied strategy that optimally profits from flows improves the investment performance of most existing characteristics-based anomaly portfolios.
Notre Dame, Johns Hopkins Carey, Fed Board, RUC-VUW Joint Virtual Research Workshop, Wolfe Research QES 6th NYC Quant Conference